.

app.py

@@ -22,7 +22,6 @@ def predict_product(num1, num2):
     input_text = f'{preprocess(num1)} * {preprocess(num2)} ='
     inputs = tokenizer(input_text, return_tensors='pt').to('cuda' if torch.cuda.is_available() else 'cpu')
     model.to('cuda' if torch.cuda.is_available() else 'cpu')
-    eos_token_id = tokenizer.eos_token_id
 
     input_ids = inputs['input_ids']
     input_len = input_ids.shape[-1]
@@ -55,7 +54,7 @@ def predict_product(num1, num2):
         next_token_id = generated_ids[0, -1]
         print (next_token_id)
         
-        if next_token_id.item() == eos_token_id:
+        if next_token_id.item() == tokenizer.eos_token_id:
             print ('berak')
             break
         past_key_values = outputs.past_key_values
@@ -86,7 +85,7 @@ def predict_product(num1, num2):
             if not is_correct_digit:
                 is_correct_sofar = False
             if is_correct_digit:
-                diff.append((correct_product[i], "-"))
+                diff.append((predicted_digit, "-"))
             else:
                 diff.append((predicted_digit, "+"))
         diff = diff[::-1]